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The development of the prognostic propensity score: an introduction to a method to identify optimal treatment according to individual tailoring variables when heterogeneous treatment effects are present

THE DEVELOPMENT OF THE PROGNOSTIC PROPENSITY SCORE:
AN INTRODUCTION TO A METHOD TO IDENTIFY OPTIMAL TREATMENT
ACCORDING TO INDIVIDUAL TAILORING VARIABLES WHEN
HETEROGENEOUS TREATMENT EFFECTS ARE PRESENT
by
Dana Renée Stafkey-Mailey
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirement for the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL ECONOMICS & POLICY)
December 2008
Copyright 2008 Dana Renée Stafkey-Mailey

The foundation of this dissertation is built upon the belief that treatment effects are often heterogeneous. Thus, different patients experience different outcomes on the same medication. The existence of such heterogeneity gives indication that the current clinical evidence may not be appropriate. This becomes increasingly evident when heterogeneous treatment effects (HTE) prove to be qualitative. Thus basing clinical decisions on averages could have implications on the patients' well-being, the cost of healthcare to society, and the availability of medications in the marketplace.; Hence, the Prognostic Propensity Score (PPS) method was developed with three goals in mind; (1) To identify if HTE are present, (2) To identify if HTE are quantitative or qualitative, and (3) To identify unique patient characteristics or tailoring variables when qualitative HTE are present. Accomplishing these goals will provide physicians and other decision makers with evidence that will allow them to treat patients more efficiently.; Thus, we have created the prognostic propensity score (PPS) method. The PPS is defined as the expected outcome (on control) given the individual's covariates. To calculate the PPS we regress the outcome of interest on the covariates for only those patients treated with the control (Drug A). Using the coefficients from this model and the patient characteristics, we then compute the PPS for each patient assuming that every patient is a member of the control group. We identify if treatment effects vary across subgroups by partitioning patients by PPS into strata and calculating the treatment effect within each stratum. We repeat this analysis using the alternative treatment (Drug B) as the control. Identifying and comparing the stratum that receives the optimal benefit from each treatment we determine which patient characteristics are uniquely associated with success for the individual treatments.; To demonstrate the use of the PPS, we use a sample of California Medicaid beneficiaries diagnosed with schizophrenia. Results of this study indicate that the PPS can adequately identify HTE, sufficiently differentiate quantitative and qualitative HTE and has the potential to identify tailoring variables. Ultimately, this method will allow physicians to more accurately prescribe the most beneficial treatment for each and every patient.

THE DEVELOPMENT OF THE PROGNOSTIC PROPENSITY SCORE:
AN INTRODUCTION TO A METHOD TO IDENTIFY OPTIMAL TREATMENT
ACCORDING TO INDIVIDUAL TAILORING VARIABLES WHEN
HETEROGENEOUS TREATMENT EFFECTS ARE PRESENT
by
Dana Renée Stafkey-Mailey
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirement for the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL ECONOMICS & POLICY)
December 2008
Copyright 2008 Dana Renée Stafkey-Mailey